Design & Development

From Access to Sustainability: Investigating Ways to Foster Sustainable Use of Computational Modeling in K-12 Science Classrooms

This project investigates how to support sustained engagement in computational modeling in middle school classrooms in two ways: 1) Design and develop an accessible modeling toolkit and accompanying thematically linked curricular units; and, 2) Examine how this toolkit and curriculum enable students to become sophisticated modelers and integrate modeling with other scientific practices such as physical experimentation and argumentation.

Award Number: 
2010413
Funding Period: 
Wed, 07/15/2020 to Fri, 06/30/2023
Full Description: 

Modeling is a core scientific activity in which a difficult-to-observe phenomenon is represented, e.g., visually or in a computer program. Research has shown that sustained experience with modeling contributes to sophisticated understanding, learning, and engagement of scientific practices. Computational modeling is a promising way to integrate computation and science learning. Yet computational modeling is not widely adopted in science classrooms over sustained periods of time because of difficulties such as the time required for students to become adept modelers, the need to better integrate computational modeling with other scientific practices, and the need for teachers to experience agency in using these modeling tools. This Design and Development project investigates how to support sustained engagement in computational modeling in middle school classrooms in two ways: 1) Design and develop an accessible modeling toolkit and accompanying thematically linked curricular units; and, 2) Examine how this toolkit and curriculum enable students to become sophisticated modelers and integrate modeling with other scientific practices such as physical experimentation and argumentation. The project will contribute to the conversation around how to support students and teachers to incorporate computational modeling together with valued scientific practices into their classrooms for sustained periods. For three years, the project will work with six sixth and seventh grade teachers and approximately 400 students.

Through iterative cycles of design-based research, the project will design a computational modeling tool and six curricular units for sixth and seventh-grade students. The team will work closely with two teacher co-designers to design and develop each of the six curricular units. The goal is to investigate: 1) How students become sophisticated modelers as they shift from using phenomenon-level primitives to unpacking and modifying these primitives for extended investigations; 2) How classroom norms around computational modeling develop over time. Specifically, how do student models become objects for classroom reflection and how students integrate modeling into other practices such as explanation and argumentation; 3) How data from physical experiments support students in constructing and refining models; and, 4) How sustained engagement supports students' conceptual learning and learning to model using computing tools. The team will collect and analyze video and written data, as well as log files and pre/posttests, to examine how communities of students and teachers adopt computational modeling as an integral practice in science learning. For video and text analysis, the team will use qualitative coding to detect patterns before, during, and after the activities. For the examination of logfiles from the software, the project will use learning analytics techniques such as the classification and clustering of students' sequences of actions. Finally, the team will also conduct pre/post-tests on both content and meta-modeling skills, analyzing the results with standard statistical tests.

Assessing College-Ready Computational Thinking (Collaborative Research: Wilson)

The goal of this project is to develop learning progressions and assessment items targeting computational thinking. The items will be used for a test of college-ready critical reasoning skills and will be integrated into an existing online assessment system, the Berkeley Assessment System Software.

Award Number: 
2010314
Funding Period: 
Tue, 09/01/2020 to Sat, 08/31/2024
Full Description: 

Because of the growing need for students to be college and career ready, high-quality assessments of college readiness skills are in high demand. To realize the goal of preparing students for college and careers, assessments must measure important competencies and provide rapid feedback to teachers. It is necessary to go beyond the limits of multiple-choice testing and foster the skills and thinking that lie at the core of college and career ready skills, such as computational thinking. Computational thinking is a set of valuable skills that can be used to solve problems, design systems, and understand human behavior, and is thus essential to developing a more STEM-literate public. Computational thinking is increasingly seen as a fundamental analytical skill that everyone, not just computer scientists, can use. The goal of this project is to develop learning progressions and assessment items targeting computational thinking. The items will be used for a test of college-ready critical reasoning skills and will be integrated into an existing online assessment system, the Berkeley Assessment System Software.

The project will address a set of research questions focused on 1) clarifying computational thinking constructs, 2) usability, reliability of validity of assessment items and the information they provide, 3) teachers' use of assessments, and 4) relationships to student performance. The study sample of 2,700 used for the pilot and field tests will include all levels of students in 10th through 12th grade and first year college students (both community college and university level). The target population is students in schools which are implementing the College Readiness Program (CRP) of the National Mathematics and Science Institute. In the 2020-21 academic year 54 high schools across 11 states (CA, GA, FL, ID, LA, NC, NM, OH, TX, VA, and WA) will participate. This will include high school students in Advanced Placement classes as well as non-Advanced Placement classes.  The team will use the BEAR Assessment System to develop and refine assessment materials. This system is an integrated approach to developing assessments that seeks to provide meaningful interpretations of student work relative to cognitive and developmental goals. The researchers will gather empirical evidence to develop and improve the assessment materials, and then gather reliability and validity evidence to support their use. In total, item response data will be collected from several thousand students. Student response data will be analyzed using multidimensional item response theory models.

Geological Construction of Rock Arrangements from Tectonics: Systems Modeling Across Scales

This project will create two curriculum units that use sophisticated simulations designed for students in secondary schools that integrate the study of the tectonic system and the rock genesis system. The project seeks to overcome the more typical approaches taken in earth science classrooms where such geologic processes are treated as discrete and highly predictable, rather than intertwined and dynamic.

Lead Organization(s): 
Award Number: 
2006144
Funding Period: 
Thu, 10/01/2020 to Mon, 09/30/2024
Full Description: 

Plate tectonics is the fundamental theory of geology that underlies almost all geological processes, including land and rock formation. However, the geologic processes and immense timeframes involved are often misunderstood. This study will create two curriculum units that use sophisticated simulations designed for students in secondary schools. The simulations will integrate the study of the tectonic system and the rock genesis system. Data from the simulations would be students' sources of evidence. For instance, the Tectonic Rock Explorer would use a sophisticated modeling engine that uses the physics involved in geodynamic data to represent compressional and tensional forces and calculate pressure and temperature in rock forming environments. This project seeks to overcome the more typical approaches taken in earth science classrooms where such geologic processes are treated as discrete and highly predictable, rather than intertwined and dynamic. In addition, this study would include work on students with disabilities in earth science classrooms and explore the practices that seem to be particularly useful in helping understand these systems. By working with simulations, the researchers intend to engage students in scientific practices that are more authentic to the ways that geologists work. The researchers will study if and how these simulations and the computer-based tools allow students to observe and manipulate processes that would be may otherwise be inaccessible.

This work follows on from prior work done by the Concord Consortium on simulations of earth systems. The design and development progression in Years 1 and 2 would create two units. The first module focuses on the relationship between tectonic movement and rock formation. The second would investigate geochronology and dating of rock formations. The researchers would work with 3 teachers (and classes), and then 15 teachers (and classes) using automated data logs, class observations, and video of students working in groups in Years 1 and 2. Professional development for teachers would be followed by the creation of educative materials. Researchers will also develop the framework for an assessment tool that includes understanding of geologic terms and embedded assessments. The researchers will used a mixed methods approach to analyze student data, including analyses cycles of analysis of students pre- and post-test scores on targeted concepts, reports of student performances on tasks embedded in the simulations, and the coding of videos to analyze discourse between partners and the supports provided by teachers. Teacher data will be analyzed using interviews, surveys and journals, with some special focus on how they are seeing students with identified disabilities respond to the materials and simulations. The research team intends to make materials widely available to thousands of students through their networks and webpages, and pursue outreach and dissemination in scholarly and practitioner conferences and publications.

Reaching Across the Hallway: An Interdisciplinary Approach to Teaching Computer Science in Rural Schools

This project will develop, test, and refine a "train-the-trainer" professional development model for rural teacher-leaders. The project goal is to design and develop a professional development model that supports teachers integrating culturally relevant computer science skills and practices into their middle school social studies classrooms, thereby broadening rural students' participation in computer science.

Lead Organization(s): 
Award Number: 
2010256
Funding Period: 
Wed, 07/01/2020 to Sun, 06/30/2024
Full Description: 

Strengthening computer science (CS) and computational thinking (CT) education is a national priority with particular attention to increasing the number of teachers prepared to deliver computer science courses. For rural schools, that collectively serve more than 10 million students, it is especially challenging. Rural schools find it difficult to recruit and retain STEM teachers that are prepared to teach computer science and computational thinking. This project will develop, test, and refine a "train-the-trainer" professional development model for rural teacher-leaders. The project will build teachers' self-efficacy to deliver computer science concepts and practices into middle school social studies classrooms. The project is led by CodeVA (a statewide non-profit in Virginia), in partnership with TERC (a STEM-focused national research institution) and the University of South Florida College of Education, and in collaboration with six rural school districts in Virginia. The project goal is to design and develop a professional development model that supports teachers integrating culturally relevant computer science skills and practices into their middle school social studies classrooms, thereby broadening rural students' participation in computer science. The professional development model will be designed and developed around meeting rural teachers, where they are, geographically, economically, and culturally. The model will also be sustainable and will work within the resource constraints of the rural school district. The model will also be built on strategies that will broadly spread CS education while building rural capacity.

The project will use a mixed-methods research approach to understand the model's potential to build capacity for teaching CS in rural schools. The research design is broken down into four distinct phases; planning/development prototyping, piloting and initial dissemination, an efficacy study, and analysis, and dissemination. The project will recruit 45 teacher-leaders and one district-level instructional coach, 6th and 7th-grade teachers, and serve over 1900 6th and 7th-grade students. Participants will be recruited from the rural Virginia school districts of Buchanan, Russell, Charlotte, Halifax, and Northampton. The research question for phase 1 is what is each district's existing practice around computer science education (if any) and social studies education? Phases 2, 3 and 4 research will examine the effectiveness of professional development on teacher leadership and the CS curricular integration. Phase 4 research will examine teacher efficacy to implement the professional development independently, enabling district teachers to integrate CS into their social studies classes. Teacher data sources for each phase include interviews with administrators and teachers, teacher readiness surveys, observations, an examination of artifacts, and CS/CT content interviews. Student data will consist of classroom observation and student attitude surveys. Quantitative and qualitative data will be triangulated to address each set of research questions and provide a reliability check on findings. Qualitative data, such as observations/video, and interview data will be analyzed through codes that represent expected themes and patterns related to teachers' and coaches' experiences. Project results will be communicated through presentations at conferences such as Special Interest Group on Computer Science Education, the Computer Science Teachers Association (CSTA), the National Council for Social Studies (NCSS), and the American Educational Research Association. Lesson plans will be made available on the project website, and links will be provided through publications and newsletters such as the NCSS Middle-Level Learner, NCSS Social Education, CSTA the Voice, the NSF-funded CADREK12 website and the NSF-funded STEM Video Showcase.

Supporting Students' Language, Knowledge, and Culture through Science

This project will test and refine a teaching model that brings together current research about the role of language in science learning, the role of cultural connections in students' science engagement, and how students' science knowledge builds over time. The outcome of this project will be to provide an integrated framework that can guide current and future science teachers in preparing all students with the conceptual and linguistic practices they will need to succeed in school and in the workplace.

Lead Organization(s): 
Award Number: 
2010633
Funding Period: 
Tue, 09/01/2020 to Sat, 08/31/2024
Full Description: 

The Language, Culture, and Knowledge-building through Science project seeks to explore and positively influence the work of science teachers at the intersection of three significant and ongoing challenges affecting U.S. STEM education. First, U.S. student demographics are rapidly changing, with an increasing number of students learning STEM subjects in their second language. This change means that all teachers need new skills for meeting students where they currently are, linguistically, culturally, and in terms of prior science knowledge. Second, the needs and opportunities of the national STEM workforce are changing rapidly within a shifting employment landscape. This shift means that teachers need to better understand future job opportunities and the knowledge and skills that will be necessary in those careers. Third, academic expectations in schools have changed, driven by changes in education standards. These new expectations mean that teachers need new skills to support all students to master a range of practices that are both conceptual and linguistic. To address these challenges, teachers require new models that bring together current research about the role of language in science learning, the role of cultural connections in students' science engagement, and how students' science knowledge builds over time. This project begins with such an initial model, developed collaboratively with science teachers in a prior project. The model will be rigorously tested and refined in a new geographic and demographic context. The outcome will be to provide an integrated framework that can guide current and future science teachers in preparing all students with the conceptual and linguistic practices they will need to succeed in school and in the workplace.

This project model starts with three theoretical constructs that have been integrated into an innovative framework of nine practices. These practices guide teachers in how to simultaneously support students' language development, cultural sustenance, and knowledge building through science with a focus on supporting and challenging multilingual learners. The project uses a functional view of language development, which highlights the need to support students in understanding both how and why to make shifts in language use. For example, students' attention will be drawn to differences in language use when they shift from language that is suited to peer negotiation in a lab group to written explanations suitable for a lab report. Moving beyond a funds of knowledge approach to culture, the team view of integrating students' cultural knowledge includes strengthening the role of home knowledge in school, but also guiding students to apply school knowledge to their out-of-school interests and passions. Finally, the project team's view of cumulative knowledge building, informed by work in the sociology of knowledge, highlights the need for teachers and students to understand the norms for meaning making within a given discipline. In the case of science, the three-dimensional learning model in the Next Generation Science Standards makes these disciplinary norms visible and serves as a launching point for the project's work. Teachers will be supported to structure learning opportunities that highlight what is unique about meaning making through science. Using a range of data collection and analysis methods, the project team will study changes in teachers' practices and beliefs related to language, culture and knowledge building, as teachers work with all students, and particularly with multilingual learners. The project work will take place in both classrooms and out of class science learning settings. By working closely over several years with a group of fifty science teachers spread across the state of Oregon, the project team will develop a typology of teachers (design personas) to increase the field's understanding of how to support different teachers, given their own backgrounds, in preparing all students for the broad range of academic and occupational pathways they will encounter.

Supporting Elementary Teacher Learning for Effective School-Based Citizen Science (TL4CS)

This project will develop two forms of support for teachers: guidance embedded in citizen science project materials and teacher professional development. The overarching goal of the project is to generate knowledge about teacher learning that enables elementary school citizen science to support students' engagement with authentic science content and practices through data collection and sense making.

Lead Organization(s): 
Award Number: 
2009212
Funding Period: 
Wed, 07/01/2020 to Sun, 06/30/2024
Full Description: 

Citizen science involves individuals, who are not professional scientists, in authentic scientific research, typically in collaboration with professional scientists. When implemented well in elementary schools, citizen science projects immerse students in science content and engage them with scientific practices. These projects can also create opportunities for students to connect with their local natural surroundings, which is needed, as some research has suggested that children are becoming increasingly detached from nature. The classroom teacher plays a critical role in ensuring that school-based citizen science projects are implemented in a way that maximizes the benefits. However, these projects typically do not include substantial guidance for teachers who want to implement the projects for instructional purposes. This project will develop two forms of support for teachers: (1) guidance embedded in citizen science project materials and (2) teacher professional development. It will develop materials and professional development experiences to support teacher learning for 80 5th grade teachers impacting students in 40 diverse elementary schools.

The overarching goal of this project is to generate knowledge about teacher learning that enables elementary school citizen science to support students' engagement with authentic science content and practices through data collection and sense making. Specifically, the study is designed to address the following research questions: (1) What kinds of support foster teacher learning for enacting effective school-based citizen science? (2) How do supports for teacher learning shape the way teachers enact school-based citizen science? and (3) What is the potential of school-based citizen science for positively influencing student learning and student attitudes toward nature and science? Data collected during project implementation will include teacher surveys, student surveys and assessments, and case study protocols.

How Deep Structural Modeling Supports Learning with Big Ideas in Biology (Collaborative Research: Capps)

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2010223
Funding Period: 
Sat, 08/01/2020 to Wed, 07/31/2024
Full Description: 

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. This need is forcefully advanced by policy leaders including the National Research Council and the College Board. They point out that learning is more effective when students organize and link information within a consistent knowledge framework, which is what big ideas should provide. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology. In DSM, students learn a big idea as the underlying, or "deep" structure of a set of examples that contain the structure, but with varying outward details. As learners begin to apprehend the deep structure (i.e., the big idea) within the examples, they use the tools and procedures of scientific modeling to express and develop it. According to theories of learning that undergird DSM, the result of this process should be a big idea that is flexible, meaningful, and easy to express, thus providing an ideal framework for making sense of new information learners encounter (i.e., learning with the big idea). To the extent that this explanation is born out in rigorous research tests and within authentic curriculum materials, it contributes important knowledge about how teaching and learning can be organized around big ideas, and not only for deep structural modeling but for other instructional approaches as well.

This project has twin research and prototype development components. Both are taking place in the context of high school biology, in nine classrooms across three districts, supporting up to 610 students. The work focuses on three design features of DSM: (1) embedding model source materials with intuitive, mechanistic ideas; (2) supporting learners to abstract those ideas as a deep structure shared by a set of sources; and (3) representing this deep structure efficiently within the model. In combination, these features support students to understand an abstract, intuitively rich, and efficient knowledge structure that they subsequently use as a framework to interpret, organize, and link disciplinary content. A series of five research studies build on one another to develop knowledge about whether and how the design features bring about these anticipated effects. Earlier studies in the sequence are small-scale classroom experiments randomly assigning students to either deep structural modeling or to parallel, non modeling controls. Measures discriminate for the anticipated effects during learning and on posttests. Later studies use qualitative methods to carefully trace the anticipated effects over time and across topics. As a group, these studies are contributing generalized knowledge of how learners can effectively abstract and represent big ideas and how these ideas can be leveraged as frameworks for learning content with understanding. Two research-tested biology curriculum prototypes are being developed as the studies evolve: a quarter-year DSM biology curriculum centered on energy; and an eighth-year DSM unit centered on natural selection.

How Deep Structural Modeling Supports Learning with Big Ideas in Biology (Collaborative Research: Shemwell)

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2010334
Funding Period: 
Sat, 08/01/2020 to Wed, 07/31/2024
Full Description: 

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. This need is forcefully advanced by policy leaders including the National Research Council and the College Board. They point out that learning is more effective when students organize and link information within a consistent knowledge framework, which is what big ideas should provide. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology. In DSM, students learn a big idea as the underlying, or "deep" structure of a set of examples that contain the structure, but with varying outward details. As learners begin to apprehend the deep structure (i.e., the big idea) within the examples, they use the tools and procedures of scientific modeling to express and develop it. According to theories of learning that undergird DSM, the result of this process should be a big idea that is flexible, meaningful, and easy to express, thus providing an ideal framework for making sense of new information learners encounter (i.e., learning with the big idea). To the extent that this explanation is born out in rigorous research tests and within authentic curriculum materials, it contributes important knowledge about how teaching and learning can be organized around big ideas, and not only for deep structural modeling but for other instructional approaches as well.

This project has twin research and prototype development components. Both are taking place in the context of high school biology, in nine classrooms across three districts, supporting up to 610 students. The work focuses on three design features of DSM: (1) embedding model source materials with intuitive, mechanistic ideas; (2) supporting learners to abstract those ideas as a deep structure shared by a set of sources; and (3) representing this deep structure efficiently within the model. In combination, these features support students to understand an abstract, intuitively rich, and efficient knowledge structure that they subsequently use as a framework to interpret, organize, and link disciplinary content. A series of five research studies build on one another to develop knowledge about whether and how the design features bring about these anticipated effects. Earlier studies in the sequence are small-scale classroom experiments randomly assigning students to either deep structural modeling or to parallel, non modeling controls. Measures discriminate for the anticipated effects during learning and on posttests. Later studies use qualitative methods to carefully trace the anticipated effects over time and across topics. As a group, these studies are contributing generalized knowledge of how learners can effectively abstract and represent big ideas and how these ideas can be leveraged as frameworks for learning content with understanding. Two research-tested biology curriculum prototypes are being developed as the studies evolve: a quarter-year DSM biology curriculum centered on energy; and an eighth-year DSM unit centered on natural selection.

Responsive Instruction for Emergent Bilingual Learners in Biology Classrooms

This project seeks to support emergent bilingual students in high school biology classrooms. The project team will study how teachers make sense of and use an instructional model that builds on students' cultural and linguistic strengths to teach biology in ways that are responsive. The team will also study how such a model impacts emergent bilingual students' learning of biology and scientific language practices, as well as how it supports students' identities as knowers/doers of science.

Lead Organization(s): 
Award Number: 
2010153
Funding Period: 
Wed, 07/01/2020 to Fri, 06/30/2023
Full Description: 

The population of students who are emergent bilinguals in the US is not only growing in number but also, historically, has been underrepresented in STEM fields. Emergent bilingual students have not had access to the same high-quality science education as their peers, despite bringing rich academic, linguistic and cultural strengths to their learning. Building on smaller pilot studies and ideas that have shown to be successful in supporting emergent bilingual students' learning of elementary science, this project seeks to support emergent bilingual students in high school biology classrooms. The project team will study how teachers make sense of and use an instructional model that builds on students' cultural and linguistic strengths to teach biology in ways that are responsive. The team will also study how such a model impacts emergent bilingual students' learning of biology and scientific language practices, as well as how it supports students' identities as knowers/doers of science. The collaboration will include two partner districts that will allow the project work to impact about 11,000 high school students and 30 biology teachers in Florida. Over time, the project team plans to enact and study three cohorts of teachers and students; use the information learned to improve the instructional model; and develop lessons, a website, and other materials that can be applied to other contexts to support emergent bilingual students' learning of biology. This project will increase emergent bilingual students' participation in biology classes, improve their achievement and engagement in science and engineering practices, extend current research-based practices, and document how to build on emergent bilingual students' strengths and prior experiences.

In two previous pilot studies through the collaboration of an interdisciplinary team, the project team developed an instructional model that they found supported emergent bilingual students to have high-quality opportunities for science learning. The model builds on research related to culturally responsive instruction; funds of knowledge (including work on identity affirmation and collaboration); and linguistically responsive instruction (including using students' home languages and multiple modalities, and explicit attention to academic language). Using design-based research, the project team will gather data from two primary settings: their professional development program and biology teachers' classrooms. They will use these data both to improve the instructional model and professional development for biology teachers. Additionally, the project team will study how teachers use the model to support emergent bilingual students' biology engagement and achievement, as well as study how biology teachers enact the instructional model in two school districts. The project will work toward three main outcomes: a) to develop new knowledge related to how diverse learners develop language and content knowledge in biology through engaging in science and engineering practices; b) to generate new knowledge about how biology teachers can adapt responsive instruction to local contexts and student populations; and c) to articulate an instructional model for biology teachers of emergent bilingual students that is rigorous, yet practical. The dissemination and sustainability include publishing and presenting findings at a range of conferences and journals; making available the refined instructional framework and professional development materials on a website; communication with district leaders and policymakers; and white papers that can be more widely distributed.

Parents, Teachers, and Multilingual Children Collaborating on Mathematics Together (Collaborative Research: Quintos)

The goal of this project is to develop and study a mathematics partnership that engages multilingual children, their teachers, and their parents in mathematical experiences together. The project will design professional learning opportunities for parents, teachers, and students, and study the ways in which the professional learning opportunities influence teacher beliefs, quality of instruction, parent beliefs, and teacher and parent understanding of positioning.

Award Number: 
2010417
Funding Period: 
Mon, 06/01/2020 to Fri, 05/31/2024
Full Description: 

The connections between students' home and family contexts and the activities of formal schooling are critical to support meaningful learning and family engagement in formal schooling. The need to better understand and make use of those connections is particularly important for multilingual learners whose family and cultural contexts may differ significantly from school contexts and their teachers' own experiences. The goal of this project is to develop and study a mathematics partnership that engages multilingual children, their teachers, and their parents in mathematical experiences together. These mathematical experiences are designed to advance equity in mathematics education for multilingual students. The project will design professional learning opportunities for parents, teachers, and students, and study the ways in which the professional learning opportunities influence teacher beliefs, quality of instruction, parent beliefs, and teacher and parent understanding of positioning.

This project uses a design-based implementation research (DBIR) approach, along with principles of Social Design Experiments to engage in iterative cycles of inquiry to develop, implement, and refine the model. Parents, teachers, and students in three states (Arizona, Maryland, and Missouri) will be recruited that represent diverse populations both with respect to demographics and with respect to the policy contexts surrounding multilingual learners. Two cohorts of parents will be invited to participate in the parent-teacher study group, one consisting of 6 parents and teachers per site and one consisting of 20 parents and their children's teachers per site. In each iteration, data will be collected at multiple time points related to teachers' beliefs about effective math instruction for multilingual students; quality of mathematics instruction for linguistically diverse students; focus group interviews with parents and students, and video records of teachers and parents working with their students doing mathematics during study group convenings. Data analysis will blend quantitative and qualitative methods. Quantitative methods will include t-tests, multivariate, and correlational analyses to examine changes in teacher beliefs, instructional quality, and the relationships between the two. Qualitative analyses using thematic coding and discourse analysis will be used to analyze study group meetings and outcomes related to parent and teacher positioning of multilingual learners.

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